About the company
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Data Scientist – Advanced Analytics based in the United States.
Responsibilities
- Lead the end-to-end design, execution, and analysis of marketing and product experiments, including A/B testing, multivariate testing, geographic experiments, and holdout testing.
- Define and manage the experimentation roadmap, including hypothesis development, prioritization, statistical power analysis, and success metrics.
- Develop and refine methodologies for lift measurement, incrementality testing, causal inference, and marketing effectiveness measurement.
- Establish experimentation standards, governance frameworks, and best practices to ensure statistical rigor and consistent, actionable insights.
- Design, build, validate, and deploy machine learning and Generative AI solutions using large-scale structured and unstructured datasets.
- Develop predictive and prescriptive models, including market mix, attribution, and uplift models, to improve business performance and measurable outcomes.
- Lead hands-on model development, coding, testing, validation, and production deployment while establishing technical standards for the broader analytics team.
- Build and maintain reliable, scalable data pipelines that support data quality, integrity, and analytical performance.
- Evaluate emerging technologies, machine learning techniques, large language models, and agent-based frameworks to identify opportunities for innovation.
- Partner with Product, Marketing, Sales, IT, Risk, and Compliance teams to identify high-value business challenges and translate them into testable hypotheses and analytical solutions.
- Communicate complex findings and recommendations clearly to technical teams, business stakeholders, and executive leadership.
- Act as a trusted subject matter expert in experimentation, measurement, advanced analytics, AI, and machine learning.
- Mentor and support other data scientists and analytics professionals through coaching, technical guidance, and knowledge sharing.
Requirements
- Master’s degree in Statistics, Data Science, Computer Science, Economics, Mathematics, Engineering, or a related quantitative discipline is required.
- PhD in Statistics, Data Science, or a related quantitative field is strongly preferred.
- At least eight years of progressive experience in data science, analytics, or machine learning, including substantial hands-on work with large-scale data environments.
- Demonstrated success leading or contributing as a senior technical expert to experimentation, measurement, and advanced analytics initiatives.
- Deep expertise in marketing experimentation, including experimental design, A/B and multivariate testing, metric development, lift measurement, and incrementality analysis.
- Strong knowledge of causal inference, hypothesis testing, statistical modeling, and statistical power analysis.
- Hands-on experience developing and deploying market mix models (MMM), attribution models, and uplift models.
- Advanced programming skills in Python, Spark/PySpark, and SQL.
- Practical experience developing and deploying machine learning models using techniques such as clustering, classification, regression, neural networks, anomaly detection, recommendation engines, and predictive modeling.
- Experience with large language models (LLMs), Generative AI solutions, and emerging agent-based frameworks such as LangChain, LangSmith, or comparable technologies.
- Familiarity with modern cloud-based data platforms, including Databricks, Snowflake, or similar data lake environments.
- Experience building and deploying analytical solutions in AWS and Azure cloud environments.
- Familiarity with containerization and development tools such as Kubernetes, Docker, and Git.
- Experience with data visualization and business intelligence tools; Tableau is preferred. Familiarity with data science platforms such as Dataiku is an advantage.
- Experience working in financial services or another highly regulated, data-intensive industry is preferred.
- Proven ability to influence senior stakeholders, collaborate across business functions, and translate complex challenges into scalable analytical solutions with measurable impact.
- Strong leadership, mentoring, communication, and storytelling skills, including the ability to present technical findings as clear, executive-level recommendations.
- Ability to navigate ambiguity, prioritize competing demands, manage multiple initiatives, and deliver results in a fast-paced environment.
- Relevant certifications in data science, machine learning, or cloud technologies are a plus.
Conditions
- Annual salary range: $170,000–$200,000.
- Eligibility for an annual bonus incentive program.
- Workplace flexibility and a collaborative working environment.
- Opportunities to shape advanced analytics strategy.